All models comparison table. by Meili Liu (327309)

“…</p><p>Methods</p><p>Public gene expression datasets were analyzed to identify differentially expressed genes (DEGs) common to both RA and UC. Functional enrichment and immune infiltration analyses revealed dysregulated pathways. …”

Table 2_Functional and clinical validation of tsRNA-defined molecular subtypes guides precision therapy in gastric cancer.xlsx by Ye Tian (220278)

“…A prognostic model was constructed using machine learning algorithms and validated across multiple cohorts. The functional role of a key tsRNA, tsRNA-Asp-3-0024, was investigated through Pandora-seq, qRT-PCR, and in vitro and organoid-based assays.…”

Image 3_Functional and clinical validation of tsRNA-defined molecular subtypes guides precision therapy in gastric cancer.tif by Ye Tian (220278)

“…A prognostic model was constructed using machine learning algorithms and validated across multiple cohorts. The functional role of a key tsRNA, tsRNA-Asp-3-0024, was investigated through Pandora-seq, qRT-PCR, and in vitro and organoid-based assays.…”

Table 4_Functional and clinical validation of tsRNA-defined molecular subtypes guides precision therapy in gastric cancer.xlsx by Ye Tian (220278)

“…A prognostic model was constructed using machine learning algorithms and validated across multiple cohorts. The functional role of a key tsRNA, tsRNA-Asp-3-0024, was investigated through Pandora-seq, qRT-PCR, and in vitro and organoid-based assays.…”

Table 1_Functional and clinical validation of tsRNA-defined molecular subtypes guides precision therapy in gastric cancer.xlsx by Ye Tian (220278)

“…A prognostic model was constructed using machine learning algorithms and validated across multiple cohorts. The functional role of a key tsRNA, tsRNA-Asp-3-0024, was investigated through Pandora-seq, qRT-PCR, and in vitro and organoid-based assays.…”

Image 4_Functional and clinical validation of tsRNA-defined molecular subtypes guides precision therapy in gastric cancer.tif by Ye Tian (220278)

“…A prognostic model was constructed using machine learning algorithms and validated across multiple cohorts. The functional role of a key tsRNA, tsRNA-Asp-3-0024, was investigated through Pandora-seq, qRT-PCR, and in vitro and organoid-based assays.…”

Table 3_Functional and clinical validation of tsRNA-defined molecular subtypes guides precision therapy in gastric cancer.xlsx by Ye Tian (220278)

“…A prognostic model was constructed using machine learning algorithms and validated across multiple cohorts. The functional role of a key tsRNA, tsRNA-Asp-3-0024, was investigated through Pandora-seq, qRT-PCR, and in vitro and organoid-based assays.…”

Image 6_Functional and clinical validation of tsRNA-defined molecular subtypes guides precision therapy in gastric cancer.tif by Ye Tian (220278)

“…A prognostic model was constructed using machine learning algorithms and validated across multiple cohorts. The functional role of a key tsRNA, tsRNA-Asp-3-0024, was investigated through Pandora-seq, qRT-PCR, and in vitro and organoid-based assays.…”

Image 1_Functional and clinical validation of tsRNA-defined molecular subtypes guides precision therapy in gastric cancer.tif by Ye Tian (220278)

“…A prognostic model was constructed using machine learning algorithms and validated across multiple cohorts. The functional role of a key tsRNA, tsRNA-Asp-3-0024, was investigated through Pandora-seq, qRT-PCR, and in vitro and organoid-based assays.…”

Image 2_Functional and clinical validation of tsRNA-defined molecular subtypes guides precision therapy in gastric cancer.tif by Ye Tian (220278)

“…A prognostic model was constructed using machine learning algorithms and validated across multiple cohorts. The functional role of a key tsRNA, tsRNA-Asp-3-0024, was investigated through Pandora-seq, qRT-PCR, and in vitro and organoid-based assays.…”

Image 5_Functional and clinical validation of tsRNA-defined molecular subtypes guides precision therapy in gastric cancer.tif by Ye Tian (220278)

“…A prognostic model was constructed using machine learning algorithms and validated across multiple cohorts. The functional role of a key tsRNA, tsRNA-Asp-3-0024, was investigated through Pandora-seq, qRT-PCR, and in vitro and organoid-based assays.…”

Supplementary file 1_Hamiltonian formulations of centroid-based clustering.pdf by Myeonghwan Seong (21159605)

“…However, defining similarity is often ambiguous, making it challenging to determine the most appropriate objective function for a given dataset. Traditional clustering methods, such as the k-means algorithm and weighted maximum k-cut, focus on specific objectives—typically relying on average or pairwise characteristics of the data—leading to performance that is highly data-dependent. …”

Table 8_Integrative single-cell and spatial transcriptomics analysis reveals FLAD1 as a regulator of the immune microenvironment in hepatocellular carcinoma.xlsx by Peng Zhu (277243)

“…A modeling approach using 92 combinations of nine machine learning algorithms was applied, producing a predictive model with good performance. …”

Table 9_Integrative single-cell and spatial transcriptomics analysis reveals FLAD1 as a regulator of the immune microenvironment in hepatocellular carcinoma.xlsx by Peng Zhu (277243)

“…A modeling approach using 92 combinations of nine machine learning algorithms was applied, producing a predictive model with good performance. …”

Table 4_Integrative single-cell and spatial transcriptomics analysis reveals FLAD1 as a regulator of the immune microenvironment in hepatocellular carcinoma.xlsx by Peng Zhu (277243)

“…A modeling approach using 92 combinations of nine machine learning algorithms was applied, producing a predictive model with good performance. …”

Table 1_Integrative single-cell and spatial transcriptomics analysis reveals FLAD1 as a regulator of the immune microenvironment in hepatocellular carcinoma.xlsx by Peng Zhu (277243)

“…A modeling approach using 92 combinations of nine machine learning algorithms was applied, producing a predictive model with good performance. …”

Image 1_Integrative single-cell and spatial transcriptomics analysis reveals FLAD1 as a regulator of the immune microenvironment in hepatocellular carcinoma.tif by Peng Zhu (277243)

“…A modeling approach using 92 combinations of nine machine learning algorithms was applied, producing a predictive model with good performance. …”

Table 3_Integrative single-cell and spatial transcriptomics analysis reveals FLAD1 as a regulator of the immune microenvironment in hepatocellular carcinoma.xlsx by Peng Zhu (277243)

“…A modeling approach using 92 combinations of nine machine learning algorithms was applied, producing a predictive model with good performance. …”

Table 7_Integrative single-cell and spatial transcriptomics analysis reveals FLAD1 as a regulator of the immune microenvironment in hepatocellular carcinoma.xlsx by Peng Zhu (277243)

“…A modeling approach using 92 combinations of nine machine learning algorithms was applied, producing a predictive model with good performance. …”

Table 10_Integrative single-cell and spatial transcriptomics analysis reveals FLAD1 as a regulator of the immune microenvironment in hepatocellular carcinoma.xlsx by Peng Zhu (277243)

“…A modeling approach using 92 combinations of nine machine learning algorithms was applied, producing a predictive model with good performance. …”